基于扩展卡尔曼滤波算法的室内定位跟踪系统
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国家自然科学基金资助项目(61572366,61303209);皖西学院校级项目(WXZR1503,WXZR1524)


Wireless indoor positioning system based on extended Kalman filtering algorithm
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    摘要:

    为了解决无线室内定位系统实时跟踪位置坐标误差较大问题,提出一种基于扩展卡尔曼滤波(EKF)算法的室内定位方法。系统采用基于WiFi信号指纹定位,然后利用扩展卡尔曼滤波对估算的位置进行滤波,以改善WiFi指纹定位方法的精度,达到对目标实时跟踪。仿真和实验结果表明,该算法有效地改善了系统定位精度,能较好地满足室内定位的需求。

    Abstract:

    An indoor the real-time positioning technology based on Extended Kalman Filtering (EKF) algorithm is proposed to solve the problem that the forecasted position error is larger. Systems based on fingerprint positioning WiFi signal, and the Kalman filter is used to filter the forecasted location in order to improve the accuracy of WiFi fingerprinting positioning method, to achieve real-time tracking of the target. The simulation and experimental results illustrate that method improves the positioning precision, can better fulfil requirements of indoor positioning.

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凌海波,周先存.基于扩展卡尔曼滤波算法的室内定位跟踪系统[J].河北工程大学自然版,2016,33(2):108-112

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  • 收稿日期:2016-03-30
  • 在线发布日期: 2016-06-29
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